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Backcasting the Future of the Automotive Industry: Leveraging Digital Technologies for the Circular Economy
No full textThe automotive industry faces environmental challenges due to fossil fuels reliance and linear production models. Transitioning to a circular economy (CE) is essential for reducing emissions and achieving sustainability. This study uses backcasting to envision a circular automotive industry by 2050, aligned with the European Green Deal’s carbon neutrality objectives. Our envisioned future leverages digital technologies like AI, digital twins, and product passports to enhance data sharing, traceability, and decision making across the supply chain. We examine how these technologies improve lifecycle management of electric vehicles, enhance circularity in design and manufacturing, and ensure transparency from production to end-of-life. While these technologies extend product lifecycles and minimize waste, transitioning towards circularity presents challenges such as data sharing, emphasizing the need for collaborative industry platforms. By engaging key stakeholders, we developed a pathway from the current state to the envisioned circular future. Focusing on CE principles, the study seeks to foster a systemic shift towards circularity, bridging the gap between information systems and CE research. Strategic policy interventions and cooperative frameworks are recommended to enable the transition. The paper contributes insights into digitalization’s impact on CE, providing actionable strategies for industry stakeholders aiming to implement sustainable practices amid global resource constraints
The Implications of AI and Generative AI for Teaching and Learning
No full textGAI has received significant investment and adoption across various businesses over a relatively short time period. Just as the Internet and the World Wide Web did several decades ago, GAI will substantially alter how teaching and learning are conducted and how institutions of higher education will use this technology and related tools. A function of higher education institutions is to prepare the workforce of the future. However, given that incorporating GAI in teaching and learning creates both opportunities and challenges, a major question is how faculty, students, and higher education institutions should properly adopt this rapidly changing and transformative technology. In this position paper, we propose a multi-factor framework that addresses the ethical and appropriate use of this technology in teaching and learning for faculty and students
AI-Assisted Bettors: Analyzing AI-Driven Betting Behavior through Cluster Analysis
No full textThe use of artificial intelligence (AI) systems in consumer-facing decision-support systems (DSS) such as predictive analytics and automated recommendation platforms is growing in popularity in numerous domains, including sports betting. The degree to which users interact with the output of automated systems, calibrate trust, and exhibit automation bias–consistent behavior is largely unknown. In this study, we investigate the behavioral segments formed by bettors using AI-powered predictive sports betting DSS based on their shifts in confidence, risk-taking behavior, and bankroll management practices. We use survey data from a sample of 200 U.S.-based bettors and SPSS TwoStep Clustering to identify three distinct behavioral profiles: Traditional Bettors, AI-Influenced Confident Bettors, and AI-Adopting Risk-Takers, each with their own unique set of interactions with and through predictive DSS. The findings show that bettors can engage in responsible adoption through strategic bankroll management practices and a tempering of AI trust, while overreliance behaviors can be mitigated or amplified, respectively, by counter or co-aligning with individual differences. Framing betting platforms as real-time, in-the-wild, and consumer-deployed DSS contributes to IS research on algorithmic decision environments, user trust, and human–computer interaction. The results advance IS theory by contributing to the discussion of how cognitive biases, human decision behaviors, and confidence amplification in and through automated systems manifest in such domains. We conclude the paper with implications for responsible DSS design and deployment as well as practical guidelines for user segmentation in predictive analytics DSS environments
From Users to Innovators: Making the Case for Lead UX in IS
No full textThis viewpoint article argues that Information Systems (IS) professionals must evolve their design practices to effectively harness insights from user-generated content (UGC). While participatory and user-centered design remain foundational, they struggle to scale and anticipate emerging needs in today’s dynamic digital ecosystems. We introduce the Lead UX framework, which integrates von Hippel’s lead user theory with data-analytic approaches to systematically identify both innovation-driving lead users and key emergent lead topics within large-scale user discussions. By combining automated topic modeling and related natural language processing techniques with expert human review, Lead UX enables IS professionals to transform overwhelming volumes of UGC into actionable intelligence for proactive, innovation-driven design. We outline a hybrid workflow for operationalizing Lead UX, address challenges such as data quality and analytic bias, and propose future research directions, including comparative case studies, practitioner assessments, and algorithmic benchmarking. Finally, we offer actionable recommendations for educators and practitioners on embedding Lead UX into curricula and development processes, positioning users as co-designers in continuous IS innovation
Do Financial Literacy and Social Networks Enhance Inclusion Through the Use of Financial Technology?
No full textThis paper explores how financial literacy and social networks reinforce the impact of financial technology, particularly mobile money, as a driver of financial inclusion and development. It also investigates how social networks, understood as interdependence among individuals, shape financial literacy and influence customer behaviors such as perceived value, customer engagement, and continuance intention, ultimately contributing to financial inclusion in terms of access, quality, usage, and welfare. Drawing on social network theory and prior research on financial literacy, financial inclusion, and technology post-adoption, the paper develops a conceptual research model and tests it using partial least squares structural equation modeling based on data from 481 mobile money users. The findings indicate that subjective financial knowledge and financial capability influence perceived value, and that financial capability and perceived value, in turn, impact customer engagement and continuance intention. Customer engagement and continuance intention are the main predictors of financial inclusion, while interdependence is the most prominent predictor of financial literacy. This paper offers an innovative perspective by adopting a context-specific theoretical approach in the field of information and communication technologies for development (ICT4D). We make a significant contribution to the literature by demonstrating how the combination of technological, educational, and social factors amplifies the benefits of mobile money from an ICT4D perspective, thereby extending its reach and impact
Navigating Artificial Intelligence for Sustainability in Organizations: Untangling Organizational, Technical, and Sustainable Characteristics through a Taxonomy
No full textWhile the transformative potentials of artificial intelligence (AI) for achieving the United Nations’ Sustainable Development Goals (SDGs) are increasingly being acknowledged, the organizational adoption of AI lags behind. With ample research on AI for sustainability (AI4S), the field’s current fragmentation hinders cumulative theorizing and orchestrated research in academia and limits practitioners’ ability to assess which AI4S use cases align with their capabilities and strategic objectives. This study addresses the gap in understanding how AI4S unfolds in organizational contexts. While the research has provided insights into technical and sustainability dimensions, we have lacked a comprehensive framework that integrates organizational adoption. We conduct a systematic literature review of 158 AI4S use cases, categorizing them into a taxonomy with 3 meta-dimensions: technological, organizational, and sustainability, 10 dimensions, and 47 characteristics. Through this analysis, we identify seven novel archetypes of AI4S, each illustrating distinct pathways for organizational innovation that align with sustainable development objectives. These archetypes offer a structured framework for researchers to investigate adoption patterns across industries and guide practitioners in designing AI4S initiatives, thereby empowering organizational stakeholders to harness AI’s full potentials to help achieve the UN SDGs
Keep CAIS Contrarian, Eccentric, and “Weird”
No full textThis editorial expresses opinions of a former Editor in Chief of CAIS reflecting a few years after completing his term. This reflection will focus on (1) replication research; (2) reasons to ignore typical metrics like citation counts and acceptance rates; (3) the journal as a “boundary spanner”; and (4) what it means to serve a global constituency. It includes some general recommendations that various stakeholders (readers, authors, associate editors, reviewers) can interpret from their own perspectives
Celebrating - And Looking Forward to - the Next 25 Years
No full textIn this 25th anniversary editorial by the current editors-in-chief, we reflect on how CAIS has evolved and changed while preserving its core mission and values. We then consider current trends and challenges in the academic publishing ecosystem and how they might impact CAIS. We conclude with some predictions for the next 25 years
Alike but Apart: Tie Decay in Social Commerce
No full textTies between users play a fundamental role in the operation of social commerce, allowing product information to diffuse from sellers to (indirectly connected) customers. However, social commerce ties are mainly formed based on customers’ interests in products, rendering them fragile. This study investigates the impacts of sellers’ promotional activities on the decay of ties in social commerce. Drawing on utility theory, we posit an inverted U-shaped relationship between the alignment of sellers’ promotions with customers’ interests and tie strength due to customers’ trade-off between surprise and fit in their consumption of product information. Moreover, we argue that the interest alignment effect is reinforced by multiple promotions (i.e., promotion count), flattening the nonlinearity of the inverted U-shaped impact and pushing the turning point to the right. We confirm these arguments via dyadic empirical analyses of a large Chinese social commerce website. The results inform social commerce practitioners of what is central to success and offer significant theoretical implications
Transforming Digital Financial Inclusion into Inclusive Development: The Critical Role of Financial Literacy
No full textThis study examines the relationships among digital financial inclusion drivers, financial literacy, institutional support frameworks, and inclusive growth outcomes in India. Despite significant policy efforts to expand digital account ownership through initiatives such as the Pradhan Mantri Jan Dhan Yojana and the Unified Payments Interface, gaps persist in translating access into developmental outcomes. Drawing on the Capability Approach, Institutional Theory, and Diffusion of Innovations Theory, the research investigates whether digital access drives inclusive growth or requires complementary mechanisms. Data were collected from 3,120 banked individuals across six Northern Indian states between November 2022 and April 2025 using stratified random sampling. Partial Least Squares Structural Equation Modeling was used to test the hypothesised relationships. Findings reveal that digital access does not directly influence inclusive growth; rather, financial literacy fully mediates this relationship, explaining the role of technology in capability conversion. Institutional support frameworks independently contribute to inclusive growth, highlighting the importance of policies, programs, and schemes. The model explains 89.8% of the variance in inclusive growth, with financial literacy as the strongest predictor. These results advance Information Technology for Development theory by demonstrating complementarity between technology, capabilities, and institutions, addressing digital divide debates by emphasizing capability formation and institutional support over access alone